Coordinate MATLAB-driven data capture and analysis for STM32 J-Link HSS workflows.
npx skills add https://github.com/Sonder4/STM32-BFD-Kit --skill bfd-matlab-mcd
Please help me install this Agent Skill. Skill: bfd-matlab-mcd Source: https://github.com/Sonder4/STM32-BFD-Kit/tree/main/skills/claude/bfd-matlab-mcd Command: npx skills add https://github.com/Sonder4/STM32-BFD-Kit --skill bfd-matlab-mcd
This skill enables end-to-end MATLAB-driven data capture and analysis for STM32 systems using J-Link HSS, supporting efficient experimentation, parameter estimation, and model iteration.
Run the MATLAB-based experiment workflow against an STM32 project and capture HSS data for system identification.
High-intent search queries and answers about installing and using this skill.
STM32 system identification with MATLAB uses closed-loop data capture via J-Link HSS. This approach captures synchronized MCU data and stores runs as reproducible datasets with manifests for parameter estimation and model iteration.
Yes, J-Link HSS supports capturing MCU data directly for MATLAB-based controller tuning. You can run Kalman, PID, LQR, or MPC tuning and perform code-generation checks within your MATLAB and Simulink workflows.
Before capturing STM32 data for MATLAB processing, you need BFD-Kit MATLAB tooling, J-Link HSS support, dataset logging, and manifest generation. These coordinate the end-to-end pipeline for synchronized scalar capture and analysis.
Experiment management for STM32 system identification stores capture runs as reproducible datasets. It generates dataset manifests and summaries alongside synchronized scalar data, ensuring efficient model iteration and parameter estimation.
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